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Boolean-Based (k, n, m) Multi-Secret Image Sharing

Authors: Chien-Chang Chen; Cheng-Shian Lin; Jia-Zhan Chen;

Boolean-Based (k, n, m) Multi-Secret Image Sharing

Abstract

Multi-secret image sharing technology shares multiple secret images among shared images for participants and the recovery requires enough shared images for fulfilling the security property. Simultaneously, the adopted Boolean method preserves high performance. The proposed (k, n, m) multi-secret image sharing scheme shares m secret images among n participants and gathering k participants’ shared images perfectly recovers these m secret images. The proposed scheme exhibits high performance because of the usage of Boolean-based processing. Moreover, the usage of a sharing matrix based strategy acquires perfect reconstruction of the secret images under (k, n) thresholds. Two proposed schemes, the source-random-mixed (SRM) and the source-random-separate (SRS) methods, are presented in this study from different strategies of sharing the random image mixed with the secret images or separated to the secret images, respectively. Moreover, the proposed SRS method exhibits the better sharing capacity. Experimental results show that the proposed schemes perform well on sharing efficiency and security.

Related Organizations
Keywords

multiple sharing, secret image sharing, QA1-939, Boolean-based, Mathematics

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    popularity
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    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
6
Top 10%
Average
Top 10%
gold